Ecological coherence of marine protected area networks: a spatial assessment using species distribution models

Abstract

Summary1. The juvenile stages of fish are often dependent on specific habitat types for their survival. Protecting these habitats may be crucial for maintaining strong adult stocks. The Natura 2000 network of the European Union offers protection of marine habitats that are essential for the recruitment of many fish species. By protecting these critical habitats the network may be important for maintaining the stocks of these fish species.2. We present a spatially explicit, GIS-based, assessment of two important components of the ecological coherence of Marine Protected Area (MPA) networks: representativity and connectivity. Representativity can be measured as the proportion of each conservation feature that is protected, whereas connectivity assesses the spatial configuration of the network. We apply these analyses to study the ecological coherence of the Natura 2000 network in a 30 000-km 2 archipelago in the Baltic Sea, with respect to a coastal fish assemblage and associated habitats. The analyses are based on fish distribution maps that have been constructed by statistically relating life stage specific occurrence to environmental variables, and thereafter making spatial predictions based on maps of the environmental variables. 3. The map-based analyses show that both the representativity and the connectivity of the network are poor with respect to the studied fish species. In total, 3AE5% (11 km 2 ) of the assemblage recruitment habitat was protected and 48% of the potentially connected habitats were included in the MPA network. 4. The assessment explicitly identified geographical areas, visually communicated using maps, where the network should be improved to ensure ecological coherence. 5. Synthesis and applications. Many MPA networks around the world, such as the Natura 2000 network in Europe, have recently come into effect. Establishment of the networks has often been governed by opportunity rather than by strict ecological analyses, primarily because distribution maps of species and habitats have been unavailable. Map-based assessments of the strengths and weaknesses of evolving MPA networks, such as the one presented here, are needed in adaptive management. They can provide an efficient tool for visualising and communicating the results to stakeholders and policy makers in the process of working towards ecological coherence.

Shoreline development and degradation of coastal fish reproduction habitats

“…Pike, perch, and roach reproduction habitats had previously been mapped using predictive species distribution (Snickars et al 2010), and sampling of YOY pike and roach was conducted in late summer -2006(Sundblad et al 2011). The models used to predict the distribution of reproduction habitats were evaluated by their cross-validated discriminatory ability, i.e., the ability to correctly separate suitable from non-suitable habitats, using ROC-values (Sundblad et al 2011).…”

“…The models used to predict the distribution of reproduction habitats were evaluated by their cross-validated discriminatory ability, i.e., the ability to correctly separate suitable from non-suitable habitats, using ROC-values (Sundblad et al 2011). ROC-values range between 0.5 and 1 where 0.5 equals chance, and 1 is perfect discrimination.…”

“…Recent decades have, however, seen a rapid development of species distribution modeling methods, allowing researchers and managers to produce predictive maps of the underwater environment and its associated biota (Elith and Leathwick 2009). In the Baltic Sea, several recent research programs have significantly benefited our understanding and knowledge of habitat distributions in general (Al-Hamdani and Reker 2007;Bučas et al 2013;Lindegarth et al 2014) and coastal fish habitats in particular (Härmä et al 2008;Kallasvuo et al 2009;Sundblad et al 2009Sundblad et al , 2011Sundblad et al , 2013Snickars et al 2010;Bergström et al 2013). For instance, using statistical non-linear relationships between life-stage specific occurrence and environmental descriptors, Sundblad et al (2011) used predictive distribution models to map key reproduction habitats of three of the most common species in the Baltic Sea coastal fish community, northern pike (Esox lucius), Eurasian perch (Perca fluviatilis) and roach (Rutilus rutilus).…”

“…Pike and perch are large piscivores important both for ecosystem functioning and for commercial and recreational fisheries, while roach is an important benthivore and prey species for large predators. During their first year of life, all three species utilize shallow, sheltered near-shore habitats with suitable vegetation and temperature development during spring and summer (Gillet and Dubois 1995;Sandström et al 2005;Snickars et al 2009Snickars et al , 2010Sundblad et al 2011Sundblad et al , 2013. These species are all sensitive to disturbances related to boating activities, either directly or indirectly.…”

“…Nevertheless, protection of these habitats by the European Natura2000 network of protected areas is poor (Sundblad et al 2011). The two habitat types ''Large shallow inlets and bays'' (1160) and ''Coastal lagoons'' (1150), as defined by the European Habitats directive, are now classified as vulnerable and endangered, respectively, in the Baltic Sea area.…”